Abstract
Character classification is known to be one of many basic applications in the field of artificial neural networks (ANN), while data transmission with low size is important in the field of source coding. In this paper, we constructed an alphabet of 36 letters which are encoded with the Huffman algorithm and then classified with a back-propagation Feed Forward artificial neural network. Since an ANN is initialized with random weights, the performance is not always optimal. Therefore, we designed a simple genetic algorithm (SGA) that choses an ANN and optimizes its architecture to improve the recognition accuracy. The performance evaluation is given to show the effectiveness of the procedure used, where we reached an accuracy of 100%.
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References
José, C.P., Neil, R.E., Curt, W.L.: Neural and Adaptive Systems: Fundamentals through Simulation, ISBN 0-471-35167-9
Dong, X.N.: Application of Neural Networks to Character Recognition. In: Proceedings of Faculty Research Day, CSIS, Pace University (May 2007)
Motameni, M.A., et al.: Learning Flexible Neural Networks for Pattern Recognition. In: Proceedings of World Academy of Science, Engineering and Technology, vol. 21 (2007) ISSN 1307 6884
Bishop, C.: Neural Networks for Pattern Recognition. Oxford Press, Oxford (1995)
Neural Network Toolbox User’s Guide, www.mathworks.com/access/helpdesk/help/pdf_doc/nnet/nnet.pdf
Fogel, D.B.: Evolutionary Computation: Towards a New Philosophy of Machine Intelligence, p. 140. IEEE Press, New York (2000)
Lezray, O., Fournier, D., Cardot, H.: Neural Network Induction Graph for Pattern Recognition. Proceedings of Neurocomputing 57, 257–274 (2004)
Araokar S.: Visual Character Recognition using Artificial Neural Networks (2010)
Huffman, D.: Profile Background Story. Scientific American, 54–58 (September 1991)
Hamid, S., Ismail, A., Siddiqui, A.A.: Practical workbook, Information Theory. Department of Computer and Information Systems Engineering, NED University of Engineering and Technology, Karachi - 75270, Pakistan (2010)
http://en.wikipedia.org/wiki/Neural_network (visited on March 25, 2010)
Frank, A., Asuncion, A.: (UCI) Machine Learning Repository University of California, Irvine, School of Information and Computer Sciences (2010), http://archive.ics.uci.edu/ml
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Ezin, E.C., Reyes-Galaviz, O.F., Reyes-García, C.A. (2010). Recognition of Huffman Codewords with a Genetic-Neural Hybrid System. In: Sidorov, G., Hernández Aguirre, A., Reyes García, C.A. (eds) Advances in Soft Computing. MICAI 2010. Lecture Notes in Computer Science(), vol 6438. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16773-7_24
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DOI: https://doi.org/10.1007/978-3-642-16773-7_24
Publisher Name: Springer, Berlin, Heidelberg
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